Evidence map›Paper›PMID 34878090›Full record

ArticleRevista de saude publica2021

Temporal trend of tuberculosis incidence and its spatial distribution in Macapá - Amapá.

Clóvis Luciano Giacomet, Marcio Souza Santos, Thaís Zamboni Berra, Yan Mathias Alves, Luana Seles Alves, Fernanda Bruzadelli Paulino da Costa, Antonio Carlos Vieira Ramos, Juliane de Almeida Crispim, Aline Aparecida Monroe, Ione Carvalho Pinto and 6 more

Abstract read
In one paragraph

Article in Revista de saude publica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Time series of cases and treatment outcomes from tuberculosis in Sergipe, 2012-2021.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2023
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Clóvis Luciano GiacometUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0002-5473-9666
Marcio Souza SantosUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0002-4455-8490
Thaís Zamboni BerraUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0002-4163-8719
Yan Mathias AlvesUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0002-5596-0047
Luana Seles AlvesUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0003-0219-7479
Fernanda Bruzadelli Paulino da CostaUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0001-5310-5592
Antonio Carlos Vieira RamosUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0002-7862-1355
Juliane de Almeida CrispimUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0003-4642-9075
Aline Aparecida MonroeUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0003-4073-2735
Ione Carvalho PintoUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0001-7541-5591
Regina Célia FioratiUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0003-3666-9809
Marcos Augusto Moraes ArcoverdeUniversidade do Oeste do Paraná, Escola de Enfermagem. Foz do Iguaçu, PR, Brasil.ORCID http://orcid.org/0000-0001-5104-559X
Dulce GomesUniversidade de Évora. Departamento de Matemática. Évora, Portugal.ORCID http://orcid.org/0000-0001-8085-1945
Giselle Lima de FreitasUniversidades Federal de Minas Gerais. Faculdades de Enfermagem. Belo Horizonte, MG, Brasil.ORCID http://orcid.org/0000-0002-8118-8054
Mellina YamamuraUniversidades Federal de São Carlos. Faculdades de Enfermagem. São Carlos, SP, Brasil.ORCID http://orcid.org/0000-0001-5228-8788
Ricardo Alexandre ArcêncioUniversidade de São Paulo. Escola de Enfermagem de Ribeirão Preto. Ribeirão Preto, SP, Brasil.ORCID http://orcid.org/0000-0003-4792-8714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the temporal trend of tuberculosis incidence after the implementation of the rapid molecular test (RMT-TB), to identify whether tuberculosis presents seasonal variation and to classify the territory according to case density and risk areas in Macapá, Amapá.

methodsEcological study of tuberculosis cases registered in the Sistema de Informação de Agravos de Notificação (SINAN - Information System for Notifiable Diseases) between 2001 and 2017. We used the Prais-Winsten test to classify the temporal trend of incidence and the interrupted time series to identify changes in the temporal trend before and after the implementation of the rapid molecular test, and to verify seasonality in the municipality. The Kernel estimator was used to classify case density and scan statistics to identify areas of tuberculosis risk.

resultsA total of 1,730 cases were identified, with a decreasing temporal trend of tuberculosis incidence (-0.27% per month, 95%CI -0.13 to -0.41). The time series showed no change in level after the implementation of the GeneXpert®MTB/RIF molecular test; however, the incidence increased in the post-test period (+2.09% per month, 95%CI 0.92 to 3.27). Regarding the seasonal variation, it showed growth (+13.7%/month, 95%CI 4.71 to 23.87) from December to June, the rainy season - called amazon winter season -, and decrease (-9.21% per month, CI95% -1.37 to -16.63) in the other periods. We classified areas with high density of cases in the Central and Northern districts using Kernel and identified three protection clusters, SC1 (RR = 0.07), SC2 (RR = 0.23) and SC3 (RR = 0.36), and a high-risk cluster, SC4 (RR = 1.47), with the scan statistics.

conclusionThe temporal trend of tuberculosis incidence was decreasing in the time series; however, detection increased after the introduction of RMT-TB, and tuberculosis showed seasonal behavior. The case distribution was heterogeneous, with a tendency to concentrate in vulnerable and risk territories, evidencing a pattern of disease inequality in the territory.

Indexed as

TuberculosisBrazilHumansIncidenceInformation SystemsSeasons

Identifiers

PMID34878090
PMCPMC8647990

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.